Journal
AI MAGAZINE
Volume 36, Issue 1, Pages 25-38Publisher
AMER ASSOC ARTIFICIAL INTELL
DOI: 10.1609/aimag.v36i1.2565
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Funding
- National Science Foundation [1117913]
- Smithsonian American Art Museum
- Div Of Information & Intelligent Systems
- Direct For Computer & Info Scie & Enginr [1117913] Funding Source: National Science Foundation
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There is a great deal of interest in big data, focusing mostly on data set size. An equally important dimension of big data is variety, where the focus is to process highly heterogeneous data sets. We describe how we use semantics to address the problem of big data variety. We also describe Karma, a system that implements our approach and show how Karma can be applied to integrate data in the cultural heritage domain. In this use case, Karma integrates data across many museums even though the data sets from different museums are highly heterogeneous.
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